perform_scaling: Performs feature scaling without overfitting

In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting

Performs feature scaling without overfitting

Description

Performs feature scaling without overfitting

Usage

perform_scaling(X, X_scaling = NULL, scale_features = TRUE, stat_attr = FALSE)

Arguments

X	A covariate matrix.
X_scaling	Existing "X_scaling" object containing the precomputed mean and variance for each covariate. This enables reusing the scaling choice and parameters from the train set, if computing the excesses on a validation or test set, in order to avoid overfitting. This is performed automatically in the "EQRN" objects.
scale_features	Whether to rescale each input covariates to zero mean and unit variance before applying the model (recommended). If X_scaling is given, X_scaling$scaling overrides scale_features.
stat_attr	DEPRECATED. Whether to keep attributes in the returned covariate matrix itself.

Value

Named list containing:

X_excesses	the (possibly rescaled and q_feat transformed) covariate matrix,
X_scaling	object of class "X_scaling" to use for consistent scaling on future datasets.

EQRN documentation built on April 4, 2025, 12:45 a.m.